Improve existing machine learning binary classification model in Python

I need someone to review and optimise an existing training model for an ensemble binary classifier in python.

The classifier is for a lending app, with the outcome variables being ‘paid’ or ‘default’.

The data is provided in a pre-processed format, in two files:

1. A flat file with one row for each item in the training set and c.40 variables

2. A short time series of a single variable

A description will be provided for all variables.

Also provided is the existing python code of the training model. It is a basic ensemble model combining some rudimentary out-of-the-box python machine learning algorithms.

Key performance metrics will be the AUC, Precision, and Recall.

Elements that will be required:

• Improving performance of model

• Feature selection to ensure generalisation/robustness

• Cross-validation

• Better hyper-parameter tuning

• Model sensitivity testing

• Determining appropriate weights for the ensemble

Please let me know what is your bid for this work, and how long you think it will take.

The process of work, and the milestone payments, will follow this order:

1. Review of existing model and short description of plans for work. (10%)

2. Progress report at half-way (40%)

3. Final output. (50%)

The dataset and training model files will be provided once the project has been awarded.

Skills: Data Science, Machine Learning (ML), Python

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About the Employer:
( 4 reviews ) London, United Kingdom

Project ID: #19699968

41 freelancers are bidding on average $204 for this job


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